The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 04, 2022

Filed:

Nov. 08, 2019
Applicant:

Suki Ai, Inc., Redwood City, CA (US);

Inventor:

Ahmad Badary, Calgary, CA;

Assignee:

Suki AI, Inc., Redwood City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/06 (2013.01); G10L 15/05 (2013.01); G10L 15/26 (2006.01); G10L 15/02 (2006.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G10L 15/02 (2013.01); G10L 15/05 (2013.01); G10L 15/26 (2013.01); G10L 2015/025 (2013.01); G10L 2015/0633 (2013.01);
Abstract

System and method for generating disambiguated terms in automatically generated transcriptions including instructions within a knowledge domain and employing the system are disclosed. Exemplary implementations may: obtain a set of transcripts representing various speech from users; obtain indications of correlated correct and incorrect transcriptions of spoken terms within the knowledge domain; obtain a vector generation model that generates vectors for individual instances of the transcribed terms in the set of transcripts that are part of the lexicography of the knowledge domain; use the vector generation model to generate the vectors such that a first set of vectors and a second set of vectors are generated that represent the instances of the first correctly transcribed term and the first incorrectly transcribed term, respectively; and train the vector generation model to reduce spatial separation of vectors generated for instances of correlated correct and incorrect transcriptions of spoken terms within the knowledge domain.


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